Motion detection methods and image sensor devices capable of generating ranking list of regions of interest and pre-recording monitoring images

ABSTRACT

A motion detection method applied into an image sensor device includes: providing a plurality of regions of interest (ROIs) on at least one monitoring image; for each region of interest (ROI): detecting whether at least one motion event occurs within the each ROI; and determining a priority level of the each ROI according to at least one feature information of the at least one motion event; and determining an alarm schedule of the ROIs for a user according to a plurality of priority levels of the ROIs.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation application of U.S. application Ser.No. 17/326,298, filed on May 20, 2021, which is a continuation-in-partof U.S. application Ser. No. 16/924,285, filed on Jul. 9, 2020, which isa continuation application of U.S. application Ser. No. 16/431,788,filed on Jun. 5, 2019. Besides, U.S. application Ser. No. 17/326,298 isa continuation-in-part of U.S. application Ser. No. 17/151,625, filed onJan. 18, 2021, which is a continuation application of U.S. applicationSer. No. 16/833,677, filed on Mar. 30, 2020, which is a continuationapplication of U.S. application Ser. No. 16/018,025, filed on Jun. 25,2018, which is a continuation-in-part of U.S. application Ser. No.15/854,697, filed on Dec. 26, 2017. The contents of these applicationsare incorporated herein by reference.

BACKGROUND OF THE INVENTION 1. Field of the Invention

The invention relates to a security monitoring scheme, and moreparticularly to a motion detection method and an image sensor device.

2. Description of the Prior Art

Referring to FIG. 1 , it is a block diagram of a conventional videosystem including an image sensor 11 and a back end circuit 13. The imagesensor 11 is used to monitor an environmental change and output a videocompatible with the Full HD or higher resolution format to the back endcircuit 13. The back end circuit 13 records the video and then performsthe image analysis to tag image features in the recorded video.

Generally, the back end circuit 13 has higher power consumption.Nowadays, the power saving is an important issue such that the totalpower consumption of a system should be reduced as much as possible.

Accordingly, the present disclosure provides a smart photographingsystem that reduces the total power consumption by reducing data amountprocessed by a back end circuit thereof.

Please refer to FIG. 5 . FIG. 5 is a monitoring system 50 in prior art.The monitoring system 50 includes a passive detector 52 and an imagedetection device 54 electrically connected to an external host 56. Thepassive detector 52 can transmit a triggering signal to the externalhost 26 while detecting temperature variation, the external host 56wakes up by the triggering signal and then actuates the image detectiondevice 54, and the image detection device 54 executes an exposureadjustment while being actuated and starts to capture a monitoring imageor to record monitoring video. Thus, even though the passive detector 52detects the temperature variation, the image detection device 54captures the monitoring image at a later time in relation to atransmission period of the triggering signal, wakeup periods of theexternal host 16 and the image detection device 54, and an exposureadjustment period of the image detection device 54, so that themonitoring system 50 cannot record the monitoring video right after thepassive detector 52 detects an unusual state.

SUMMARY OF THE INVENTION

Therefore one of the objectives of the invention is to provide an imagesensor device and a motion detection method applied in the image sensordevice, to solve the above-mentioned problems.

The present disclosure provides a photographing device including animage sensor, a first output interface, a second output interface and aprocessor. The image sensor is configured to capture a series of imagedata. The first output interface is coupled to the image sensor, andconfigured to output a first image frame, which corresponds to a firstpart of the series of image data and has a first size. The second outputinterface is coupled to the image sensor, and configured to output asecond image frame, which corresponds to a second part of the series ofimage data and has a second size, to downstream of the photographingdevice. The processor is configured to receive the first image frame,control the image sensor to output the second image frame via the secondoutput interface when identifying the first image frame containing apredetermined feature, and add a tag to the outputted second imageframe.

The present disclosure further provides a photographing device includingan image sensor, an output interface and a processor. The image sensoris configured to capture image data. The output interface is coupled tothe image sensor, and configured to output an image frame correspondingto the image data to downstream of the photographing device. Theprocessor is coupled to the output interface and configured to receivethe image frame from the output interface, and add a tag associated witha predetermined feature to the image frame outputted to the downstreamwhen identifying the image frame containing the predetermined feature.

The present disclosure further provides a photographing device includingan image sensor, a first output interface and a second output interface.The image sensor is configured to capture image data of multiple pixels.The first output interface is coupled to the image sensor, andconfigured to output a first image frame, which corresponds to a part ofthe captured image data and has a first size. The second outputinterface is coupled to the image sensor, and configured to output asecond image frame, which corresponds to the captured image data and hasa second size, to downstream of the photographing device, wherein thesecond size is larger than the first size.

The feature tag of the present disclosure is referred to any tagsinstead of a time tag such as the moving object tag, ID tag, face tag,skin color tag, human shape tag, vehicle tag, license plate tag and soon. The tag is additional information added to pixel data of the secondimage frame.

Further, the present invention provides a motion detection device havingcapable of preventing false alarm of an infrared detector and havingadvantages of energy economy and immediate reaction for solving abovedrawbacks.

According to the claimed invention, a motion detection device is matchedwith a passive detector utilized to detect an object and to accordinglygenerate a triggering signal. The motion detection device includes animage capturing unit and an operating processor. The operating processoris electrically connected with the image capturing unit, the operatingprocessor is adapted to switch the image capturing unit from a sleepmode to a wakeup mode for motion detection while being triggered by thetriggering signal, and further to optionally actuate an external host inaccordance with an analysis result of the motion detection.

According to the claimed invention, a motion detection method is appliedto the motion detection device matched with a passive detector utilizedto detect an object and to accordingly generate a triggering signal. Themotion detection method includes receiving the triggering signal,switching an image capturing unit from a sleep mode to a wakeup mode forcapturing a first monitoring image with low quality via the triggeringsignal, analyzing the first monitoring image to determine existence ofthe object, and actuating an external host in accordance with ananalysis result of the first monitoring image.

According to the claimed invention, a motion detection device is matchedwith a passive detector utilized to detect an object and to accordinglygenerate a triggering signal. The motion detection device includes animage capturing unit and an operating processor. The operating processoris electrically connected with the image capturing unit, the operatingprocessor is adapted to switch the image capturing unit from a sleepmode to a wakeup mode for motion detection while being triggered by thetriggering signal. The image capturing unit operates in a low frame rateto determine an exposure parameter of the image capturing unit but notstores monitoring images to a memory while in the sleep mode, andoperates in a high frame rate to determine existence of the object andstores the monitoring images to the memory while in the wakeup mode.

According to the claimed invention, a motion detection device is matchedwith a passive detector utilized to detect an object and to accordinglygenerate a triggering signal. The motion detection device includes animage capturing unit and an operating processor. The operating processoris electrically connected with the image capturing unit, the operatingprocessor is adapted to switch the image capturing unit from a sleepmode to a wakeup mode for motion detection while being triggered by thetriggering signal. The image capturing unit captures and stores aplurality of monitoring images in a memory in the wakeup mode, and whenthe operating processor determines existence of the object through thestored monitoring images then the image capturing unit is switched to arecording mode to record monitoring video.

The motion detection device of the present invention is electricallyconnected between the passive detector and the external host, and themotion detection device is utilized to actuate the external host whilethe passive detector triggers the motion detection device switched fromthe sleep mode to the wakeup mode. As the motion detection device is inthe sleep mode, the motion detection device can be awaken in the lowframe rate to adjust the exposure parameter and to capture thebackground image; as the motion detection device is switched to thewakeup mode, the motion detection device is transformed into the highframe rate to capture the low quality monitoring image. The motiondetection device executes the simple image analysis via the low qualitymonitoring image for a start for determining whether to actuate theexternal host; since the motion detection device actuates the externalhost, the motion detection device captures and stores the high qualitymonitoring image, and the high quality monitoring image can be used bythe external host for the accurate image analysis and execution ofrelated application programs. The motion detection device of the presentinvention can effectively economize start-up time of the monitoringsystem without waiting for a wakeup period of the external host and anexposure adjustment period of the motion detection device.

Further, the present invention provides a smart motion detection devicewithout losing images before wakeup of a processor and a relateddetermining method for solving above drawbacks.

According to the claimed invention, a smart motion detection deviceincludes a memory, a processor having a sleep mode and a wakeup mode,and a sensor array directly coupled to the memory and furtherelectrically connected with the processor. An image captured by thesensor array is processed by the processor. The sensor array is adaptedto pre-store the image into the memory when the processor is operated inthe sleep mode, and the pre-stored image is received by the processor inthe wakeup mode. The sensor array includes a comparator adapted togenerate an alarm signal for switching the processor from the sleep modeto the wakeup mode in accordance with a comparison result of thepre-stored image.

According to the claimed invention, the smart motion detection devicefurther includes a passive sensor electrically connected with theprocessor and the sensor array, and adapted to output an alarm signalfor driving the sensor array to pre-store the image into the memory andswitching the processor from the sleep mode to the wakeup mode. Inaddition, the sensor array can include a comparator adapted to comparethe pre-stored image with a reference image, and the sensor arraypre-stores the image into the memory when intensity variation betweenthe pre-stored image and the reference image is greater than apredefined value.

According to the claimed invention, a smart motion detection device iscapable of receiving an alarm signal to monitor motion of an object. Thesmart motion detection device includes a sensor array, a memory and aprocessor. The sensor array is adapted to capture images at a first timeafter receiving with the alarm signal. The memory is directly coupled tothe sensor array and adapted to pre-store the captured images. Theprocessor is coupled to the sensor array and adapted to process thecaptured images through the memory at a second time after receiving withthe alarm signal. The second time is later than the first time.

According to the claimed invention, a determining method is applied to asmart motion detection device having a memory, a sensor array, and aprocessor coupled to the memory and the sensor array. The determiningmethod includes the processor analyzing images captured by the sensorarray when the sensor array is activated to capture the images, and theprocessor analyzing images pre-stored inside the memory when the sensorarray is not activated. The processor is enabled by an alarm signal.

According to the claimed invention, the smart motion detection deviceincludes a memory, a processor and a sensor array. The processor has asleep mode and a wakeup mode. The sensor array is directly coupled tothe memory and further electrically connected with the processor, and aplurality of images captured by the sensor array is processed by theprocessor. Images captured by the sensor array when the processor isoperated in the sleep mode are pre-stored into the memory, and imagescaptured by the sensor array when the processor is operated in thewakeup mode are transmitted to the processor.

According to the claimed invention, the smart motion detection deviceincludes a memory, a processor and a sensor array. The sensor array isdirectly coupled to the memory and further electrically connected withthe processor. The sensor array and the processor are turned off under anon-working mode. When the smart motion detection device receives atrigger signal, the sensor array directly captures and sends images tothe memory before the processor sends a request to the sensor array forreceiving the captured images.

The alarm signal may be generated by the sensor array or the passivesensor. The alarm signal is utilized to activate pre-storing operationof the sensor array and mode switching operation of the processor. Whenthe alarm signal is received, the sensor array can be activated tocapture the pre-stored image at a first time and the pre-stored image istransmitted to the memory. For waiting the duration of the processorswitched from the sleep mode to the wakeup mode, the processor whichreceives the alarm signal can send a request to the sensor array for thereal-time image and the pre-stored image at a second time later than thefirst time, so that the pre-stored image from the memory are processedlater than the first time, and the real-time image is not stored intothe memory but directly transmitted to the processor for the digitalprocessing. The smart motion detection device and the relateddetermining method of the present invention can effectively economizestart-up time of the smart motion detection device without waiting for awakeup period of the processor.

According to embodiments of the invention, a motion detection methodapplied into an image sensor device is further disclosed. The methodcomprises: providing a plurality of regions of interest (ROIs) on atleast one monitoring image; for each region of interest (ROI): detectingwhether at least one motion event occurs within the each ROI; anddetermining a priority level of the each ROI according to at least onefeature information of the at least one motion event; and determining analarm schedule of the ROIs for a user according to a plurality ofpriority levels of the ROIs.

According to the embodiments, a motion detection method applied into animage sensor device is further disclosed. The method comprises: whendetecting a first motion event within a first region of interest (ROI)on a first monitoring image generated from the image sensor device,generating a first feature information of the first motion event and afirst timestamp; searching a system storage, electrically coupled toanother different image sensor device, according to the first featureinformation and the first timestamp, to obtain a second motion eventwithin a second ROI on a second monitoring image generated from theanother different image sensor device; and using an identificationinformation of the second motion event as an identification informationof the first motion event to combine the second motion event with thefirst motion event.

According to the embodiments, an image sensor device is furtherdisclosed. The device comprises a sensing circuit and a processingcircuit. The sensing circuit is used for generating at least onemonitoring image and providing a plurality of regions of interest (ROIs)on the at least one monitoring image. The processing circuit is coupledto the sensing circuit. For each region of interest (ROI), theprocessing circuit is arranged for detecting whether at least one motionevent occurs within the each ROI, for determining a priority level ofthe each ROI according to at least one feature information of the atleast one motion event, and for determining an alarm schedule of theROIs for a user according to a plurality of priority levels of the ROIs.

According to the embodiments, an image sensor device is furtherdisclosed. The device comprises a sensing circuit and a processingcircuit. The sensing circuit is used for sensing a first monitoringimage. The processing circuit is coupled to the sensing circuit, and itis arranged for: detecting a first motion event within a first region ofinterest (ROI) on the first monitoring image generated from the sensingcircuit; generating a first feature information of the first motionevent and a first timestamp; searching a system storage, electricallycoupled to another different image sensor device, according to the firstfeature information and the first timestamp, to obtain a second motionevent within a second ROI on a second monitoring image generated fromthe another different image sensor device; and using an identificationinformation of the second motion event as an identification informationof the first motion event to combine the second motion event with thefirst motion event.

These and other objectives of the present invention will no doubt becomeobvious to those of ordinary skill in the art after reading thefollowing detailed description of the preferred embodiment that isillustrated in the various figures and drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of a conventional video system.

FIG. 2 is a block diagram of a photographing system according to oneembodiment of the present disclosure.

FIG. 3 is an operational schematic diagram of a photographing deviceaccording to one embodiment of the present disclosure.

FIG. 4 is a block diagram of a photographing system according to anotherembodiment of the present disclosure.

FIG. 5 is a monitoring system 50 in prior art.

FIG. 6 is a block diagram of a motion detection device according to anembodiment of the present invention.

FIG. 7 is a flow chart of a motion detection method applied to themotion detection device according to the embodiment of the presentinvention.

FIG. 8 is a flow chart of a motion detection method applied to themotion detection device according to the embodiment of the presentinvention.

FIG. 9 is a waveform diagram of a frame rate executed by an imagecapturing unit according to the embodiment of the present invention.

FIG. 10 is a functional block diagram of a smart motion detection deviceaccording to a first embodiment of the present invention.

FIG. 11 is a procedural diagram of the smart motion detection deviceaccording to the first embodiment of the present invention.

FIG. 12 is a functional diagram of the smart motion detection deviceaccording to a second embodiment of the present invention.

FIG. 13 is a procedural diagram of the smart motion detection deviceaccording to the second embodiment of the present invention.

FIG. 14 is a functional diagram of the smart motion detection deviceaccording to a third embodiment of the present invention.

FIG. 15 is a procedural diagram of the smart motion detection deviceaccording to the third embodiment of the present invention.

FIG. 16 is a flow char of a determining method according to theembodiment of the present invention.

FIG. 17 is a block diagram of an image sensor device applied into asecurity monitoring system according to an embodiment of the invention.

FIG. 18 is a diagram showing an example of ROIs on a monitoring imageaccording to an embodiment of the invention.

FIG. 19 is a flowchart diagram of a method of the image sensor device ofFIG. 17 according to an embodiment of the invention.

FIG. 20 is a block diagram of the image sensor device applied into thesecurity monitoring system according to another embodiment of theinvention.

FIG. 21 is a diagram of an example of multiple image sensor devicesrespectively comprised by or installed within different camera devicesbeing disposed at different locations in a security monitoring systemaccording to an embodiment of the invention.

FIG. 22 is a diagram an example of the image sensor devices according toa different embodiment of the invention.

FIG. 23 is a diagram another example of the image sensor devicesaccording to another different embodiment of the invention.

FIG. 24 is a flowchart diagram of the method of merging image streams ofdifferent image sensor devices and pre-recoding image streams accordingto an embodiment of the invention.

DETAILED DESCRIPTION

It should be noted that, wherever possible, the same reference numberswill be used throughout the drawings to refer to the same or like parts.

The present disclosure is applicable to an image processing system thattransmits captured image frames to a back end circuit forpost-processing. The image processing system is, for example, a securitymonitoring system.

One objective of the present disclosure is to reduce loading of thebacked thereby reducing total power consumption of the system. The backend is arranged to record a plurality of images (or referred to a video)outputted by a photographing device, and a video interval desired to bewatched in playing the video on a screen is selected by selecting therecorded feature tag to realize a smart photographing system.

Referring to FIG. 2 , it is a block diagram of a smart photographingsystem 200 according to one embodiment of the present disclosure,including a photographing device 20 and a back end circuit 9 coupled toeach other, wherein the back end circuit 9 has the function of imagerecording (e.g., in a memory) and playing (e.g., via a screen). The backend circuit 9 is, for example, a computer system such as a notebookcomputer, a tablet computer, a desktop computer or a central monitoringsystem. According to different applications, the back end circuit 9 hasdifferent play modes such as fast-forward, backward and selecting videotime interval. In some embodiments, the photographing system 200 recordsenvironmental sound, and the back end circuit 9 has the function ofplaying audio data.

The photographing device 20 and the back end circuit 9 are arranged as asingle device, or arranged as two separated devices coupled to eachother in a wired or wireless manner without particular limitations. Theback end circuit 9 is, for example, in a remote central server out ofthe photographing device 20.

The photographing device 20 is, for example, a sensor chip formed as anIC package, and has pins for communicating with external electronicdevices. The photographing device 20 includes an image sensor 21, afirst output interface 22, a second output interface 23 and a processor24.

The first output interface 22 is coupled to the processor 24, andoutputs first image frames Im1 having a first size to the processor 24for the image recognition and analysis. The second output interface 23is coupled to a back end circuit 9 out of the photographing device 20via the pin (not shown in figure), or by a wired or wireless connection,and outputs second image frames Im2 having a second size to the back endcircuit 9, e.g., via a signal transmission line, a bus line and/orwireless channel.

In one non-limiting embodiment, the first size is preferably muchsmaller than the second size. For example, the second size is compatiblewith the full HD format or higher formats for recording the videosuitable to be watched by users; and the first size is compatible withthe SD format or lower formats to reduce data amount processed by theprocessor 24.

The image sensor 21 is, for example, a CCD image sensor, a CMOS imagesensor or other optical sensors for converting light energy toelectrical signals. The image sensor 21 includes a plurality of pixelsfor generating image data within every frame period to the first outputinterface 22 or the second output interface 23. For example, the imagesensor 21 includes a pixel array for generating the image data, and hasa sampling circuit (e.g., CDS circuit) for sampling the image data fromevery pixel. The sampled image data is then converted into digital databy an analog to digital converter (ADC) to form the first image frameIm1 or the second image frame Im2.

The image sensor 21 captures a series of image data, corresponding tosuccessive image frame, at a predetermined frame rate. The first imageframe corresponds to a first part of the series of image data, and thesecond image frame corresponds to a second part of the series of imagedata. The first and second parts of the series of image data correspondto image data of a same image frame or different image frames.

To cause the first image frame Im1 to be smaller than the second imageframe Im2, in one aspect the first image frame Im1 is acquired withinthe frame period by turning off a part of pixels of the pixel array ofthe image sensor 21, i.e. the first image frame Im1 containing the imagedata outputted by a part of pixels of the pixel array. In anotheraspect, the first image frame is generated by downsampling the imagedata outputted by the image sensor 21, but not limited thereto. Othertechniques suitable to reduce the size of image frames outputted by animage sensor are also applicable to the present disclosure.

The processor 24 is, for example, an application specific integratedcircuit (ASIC) or a digital signal processor (DSP), and used to receivea first image frame Im1 to identify whether the first image frame Im1includes a predetermined feature. For example, when the first imageframe Im1 contains a moving object (e.g., by comparing multiple imageframes), the first image frame Im1 is identified to contain thepredetermined feature, but not limited to. The processor 24 identifies aface, a human shape, a predetermined identification (ID), apredetermined vehicle, a predetermined license plate, skin color and soon (e.g., using the machine learning or comparing with pre-storedfeatures) to indicate that the first image frame Im1 contains thepredetermined feature. When the first image frame Im contains thepredetermined feature, the processor 24 informs the image sensor 21 tooutput successive image frames (or video), i.e. the second image Im2herein, to the back end circuit 9 for the image recording.

Referring to FIG. 3 , it is a schematic diagram of several operationalaspects of the photographing device 20 according to some embodiments ofthe present disclosure. In FIG. 3 , each arrow symbol indicates oneimage frame. The first row in FIG. 3 indicates image frames generated bythe image sensor 21, and each arrow symbol in FIG. 3 indicates imagedata of one image frame is captured.

In an aspect I, when identifying that the first image frame Im1 (e.g.,image frame at time T0) contains a predetermined feature, the processor24 controls the image sensor 21 to continuously (i.e. not outputting thefirst image frame Im1) output second image frames Im2 for apredetermined interval (e.g., a time interval between T1 and T2), andadds a tag associated with the predetermined feature on every secondimage frame Im2 outputted within the predetermined interval.

The tag is included, for example, within the data header of the everysecond image frame Im2, e.g., showing by the region filled with slantlines in FIG. 2 . The tag may be different corresponding to differentimage features. For example, the tag contains at least one of a movingobject tag, an ID tag, a face tag, a skin color tag, a human shape tag,a vehicle tag and a license plate tag, but not limited thereto. Theprocessor 24 adds one or more than one tags to the second image frameIm2 according to different predetermined features using, for example, aregister 25 to change a digital value, wherein the processor 24 isarranged to tag predetermined types of different features, and a numberof said types is determined according to different applications and theprocessing ability of the processor 24.

More specifically in the aspect I, before the processor 24 identifiesthat the first image frame Im1 contains the predetermined feature, theimage sensor 21 does not output any second image frame Im2 to the backend circuit 9 via the second output interface 23. When the processor 24identifies that the first image frame Im1 contains the predeterminedfeature, it means that the photographed environment has informationdesired to be recorded such that a recording mode (e.g., between T1 andT2) is entered. In the recording mode, the back end circuit 9 recordsboth image data and tagged data of the second image frame Im2. Withinthe predetermined interval between T1 and T2, the image sensor 21 doesnot output the first image frame Im1 via the first output interface 22.To further reduce the power consumption, the processor 24 is shut downor enters a sleep mode in the recording mode.

Within the predetermined interval between T1 and T2, to normally performan auto exposure operation, the image sensor 21 further receives an autoexposure control signal AE2 from the back end circuit 9, wherein AE2 isgenerated by a processor (e.g., a CPU or MCU) of the back end circuit 9by identifying, for example, brightness of the second image frame Im2.Meanwhile, as the processor 24 is in sleeping or shut down status, theprocessor 24 does not output an auto exposure control signal AE1 (e.g.,generated by the processor 24 by identifying brightness of the firstimage frame Im1) to the image sensor 21. The auto exposure controlsignal AE1 is sent to the image sensor 21 before the recording mode isentered.

When the predetermined interval is over at T2, the image sensor 21outputs (e.g., automatically or controlled by the processor 24) thefirst image frame Im1 (e.g., image frame at time T3) to the processor 24via the first output interface 22 again. The processor 24 identifieswhether the first image frames Im1 after time T3 (including T3) containthe predetermined feature or not, and stops outputting the second imageframe Im2 to downstream of the photographing device 20 via the secondoutput interface 23. When the processor 24 further identifies one firstimage frame Im1 after time T3 contains the predetermined feature, therecording mode is entered again; and since the operation fromrecognizing the predetermined feature and entering the recording modehave been illustrated above, details thereof are not repeated herein.

In a non-limiting aspect, the first output interface 22 outputs thefirst image frame Im1 to the processor 24 from time to time(predetermined) within the predetermined interval T0-T2. If theprocessor 24 continuously identifies the predetermined feature oranother new predetermined feature within the predetermined intervalT0-T2, the processor 24 automatically extends the predetermined intervalT0-T2. More specifically, the predetermined interval T0-T2 is extendabledepending on whether any predetermined feature exists in the first imageframe Im1 within the predetermined interval T0-T2.

In an aspect II, when identifying that the first image frame Im1 (e.g.,image frame at time T0) contains a predetermined feature, the processor24 controls the image sensor 21 to alternatively output a second imageframe Im2 (e.g., image frame at time T1) via the second output interface23 and output a first image frame Im1 via the first output interface 22,and adds at least one tag, which is illustrated above and thus detailsthereof are not repeated herein, associated with the predeterminedfeature to the second image frame Im.

More specifically in the aspect II, before the processor 24 identifiesthat the first image frame Im1 contains the predetermined feature, theimage sensor 21 does not output any second image frame Im2 to downstreamof the photographing device 20 via the second output interface 23. Afterentering a recording mode (e.g., time interval between T1 and T2), theprocessor 24 receives the first image frame Im1 with a lower frequency(e.g., a half shown in FIG. 3 , but not limited thereto), and identifieswhether every received first image frame Im1 contains a predeterminedfeature, but the frame rate of the image sensor 21 is not changed. Thatis, when identifying that any first image frame Im1 contains thepredetermined feature, the processor 24 controls the image sensor 21 tooutput at least one (e.g., one being shown in FIG. 3 , but not limitedto) second image frame Im2 via the second output interface 23 to theback end circuit 9 and tags the outputted second image frame Im2,wherein the tag is determined according to a first image frame Im1 priorto the outputted second image frame Im. When identifying that thepredetermined feature disappears from the first image frame Im1 (e.g.,image frame at time T3), the processor 24 controls the image sensor 21to output the first image frame Im1 via the first output interface 22but not output the second image frame Im2 via the second outputinterface 23.

In the aspect II, within the recording mode (e.g., between T1 and T2),as the processor 24 is continuously in operation, the image sensor 21performs the auto exposure according to the auto exposure control signalAE1 from the processor 24 or according to the auto exposure controlsignal AE2 from the back end circuit 9 without particular limitations.

More specifically, in the first and second aspects, as the first imageframe Im1 and the second image frame Im2 are used for differentpurposes, the image sensor 21 does not output image frames via the firstoutput interface 22 and the second output interface 23 simultaneously.When the first image frame Im1 does not contain a predetermined feature,the photographing system 200 just continuously identifies thepredetermined feature in the first image frames Im1 but does not recordimages, e.g., the back end circuit 9 being turned off. When the firstimage frame Im1 contains the predetermined feature, second image framesIm2 are outputted continuously or separated by at least one first imageframe Im1 for the back end circuit 9 to the image recording as shown inFIG. 3 .

However in an aspect III, the first output interface 22 and the secondoutput interface 23 output a first image frame Im1 and a second imageframe Im2 in parallel, e.g., the first image frame Im1 and the secondimage frame Im2 being retrieved from the image data of the same imageframe. The processor 24 identifies whether the first image frame Im1contains a predetermined image feature. If the first image frame Im1 isidentified containing the predetermined feature, the second outputinterface 23 outputs the second image frame Im2 with at least one tag.On the contrary, if the first image frame Im1 is identified notcontaining the predetermined feature, the second output interface 23does not outputs the second image frame Im2 out of the photographingdevice 200.

In some embodiments, the smart photographing system 200 of the presentdisclosure further includes a passive infrared radiation (PIR) sensor.In this case, the processor 24 identifies whether to output the secondimage frame Im2 via the second output interface 23 to the back endcircuit 9 for the image recording according to output results of boththe PIR sensor and the image sensor 21 (e.g., one of them detecting amoving object or human body). The operation is similar to the aboveembodiments only the processor 24 further receiving the detected resultfrom the PIR sensor to accordingly identify a human body, and thusdetails thereof are not illustrated herein.

Referring to FIG. 4 , it is a schematic diagram of a photographingdevice 400 according to another embodiment of the present disclosure.The photographing device 400 includes one output interface 43 foroutputting an image frame to both the downstream circuit and theprocessor 44. The processor 44 identifies whether the image frame Imcontains a predetermined feature. If the image frame Im is identifiedcontaining the predetermined feature, the output interface 43 outputsthe image frame with at least one tag associated with the predeterminedfeature to the back end circuit 9; whereas, if the image frame Im isidentified not containing the predetermined feature, the outputinterface 43 does not output the image frame Im to the back end circuit9. That is, the output of the image frame Im to the back end circuit 9waits for the identifying process performed by the processor 24.

The operation of this embodiment also implemented using FIG. 3 , e.g.,Im1 shown in FIG. 3 is replaced by Im2. More specifically, thedifference between FIG. 4 and FIG. 2 is that in FIG. 4 , a single outputinterface 43 outputs the same image sensor Im to two directions, andthis operation is implemented by switching devices or multiplexer.

In the present disclosure, an auto exposure control signal is used tocontrol, for example, an exposure interval of the image sensor 21, lightsource intensity and a gain value to change average brightness of theimage frame generated by the image sensor 21 to be within a suitablerange.

In other embodiments, the tag indicates a simple analyzed result of thefirst image frame Im1, e.g., indicating the first image frame Im1containing a face, human skin color, a human shape object or a vehicle.The processor of the back end circuit 9 has stronger calculationability, and said processor performs the operation requiring morecalculation such as performing the ID recognition or license platerecognition according to the second image frame Im2.

As mentioned above, in the conventional security monitoring system, aback end circuit performs both the image recording and the featuretagging, and the image sensor outputs image frames having only one sizeto the back end circuit for the image recording. Accordingly, thepresent disclosure further provides a photographing device generatingimage frames of two sizes (e.g. referring to FIG. 2 ) that recognizes atriggering object in a low resolution image frame at first and thenoutputs a tagged high resolution image frame to an external back endcircuit for the image recording. As the recorded successive images havealready contained the feature tag in the data packet, the back endcircuit needs not to perform the feature tag anymore.

Please refer to FIG. 6 . FIG. 6 is a block diagram of a motion detectiondevice 60 according to an embodiment of the present invention. Themotion detection device 60 can be matched with a passive detector 62 andan external host 64 to provide preferred smart motion detectingfunction. The motion detection device 60 is electrically connectedbetween the passive detector 62 and the external host 64. The passivedetector 62 is used to detect if a specific situation happened, such asa living thing passed by or a door opened, so as to trigger the motiondetection device 60 to analyze if a true event of the specific situationexisted, which means the living thing detected by the passive detector62 is identified as an expected object. When the true event isdetermined, the motion detection device 60 transmits related data forthe external host 64 to determine a security alarm.

In one embodiment, the passive detector 62 can be a temperaturedetector, such as an infrared detector, and the motion detection device60 can be selectively operated in a sleep mode or a wakeup mode. While amonitoring region is in an usual state, the passive detector 62 does notdetect temperature variation, the motion detection device 60 stays in asleep mode; while in an unusual state that the specific situationhappens (such like the living thing passed by), the passive detector 62detects the temperature variation and generates a triggering signal toswitch the motion detection device 60 from the sleep mode to a wakeupmode.

The motion detection device 60 can include an image capturing unit 66,an operating processor 68, a memory 70 and a lighting unit 72. Theoperating processor 68 can drive the image capturing unit 66 toalternatively switch between the sleep mode and the wakeup mode, andfurther can drive the image capturing unit 66 to optionally capturemonitoring images with low quality and high quality. In one embodiment,the lighting unit 72 can be actuated only while the image capturing unit66 captures image, so as to enhance the image capturing unit 66capturing images in a power efficiency manner.

The image capturing unit 66 may capture a background monitoring imagewith a low frame rate in the sleep mode, and capture a plurality ofmonitoring images with a high frame rate in the wakeup mode. Thebackground image could be captured in low quality, wherein thebackground image is used for auto-exposure control of the imagecapturing unit 66. The monitoring images could comprise a firstmonitoring image with the low quality and a second monitoring image withthe high quality, wherein the first monitoring image is used for theoperating processor 68 to identify if the true event is happened and thesecond monitoring image is used for the external host 64 to determinethe security alarm. The monitoring images captured by the imagecapturing unit 66 can be stored inside the memory 70, and further thehigh quality monitoring image can be transmitted to the external host64.

In this embodiment, the monitoring system utilizes the passive detector62 to detect the object passing through the monitoring region for astart, and then utilizes the motion detection device 60 to analyzewhether the passed object conforms to a predetermined condition (i.e.,true event). As a view range of the passive detector 62 has passerby andthe specific situation is identified, the motion detection device 60 isswitched to the wakeup mode by the passive detector 62 and determineswhether the passerby is the expected object (which means the human); ifso, the motion detection device 60 actuates the external host 64, andthe external host 64 identifies the object within the monitoring imagesto optionally drive the motion detection device 60 in a recording mode,to transmit monitoring video, to send out a warning, to shut down themotion detection device 60 and to awaken another motion detection device60′ electrically connected with the external host 64.

Please refer to FIG. 7 . FIG. 7 is a flow chart of a motion detectionmethod applied to the motion detection device 60 according to theembodiment of the present invention. First, step S200 and S202 areexecuted to startup the monitoring system, and the passive detector 62is utilized to detect the object within the view range. If the passivedetector 62 does not detect the temperature variation, step S204 isexecuted to keep the image capturing unit 66 in the sleep mode; if thepassive detector 62 detects the temperature variation, step S206 isexecuted that the passive detector 62 transmits the triggering signal toswitch the image capturing unit 66 from the sleep mode to the wakeupmode. Then, step S208 and step S210 are executed, the lighting unit 72can be actuated in accordance with surrounding illumination and theimage capturing unit 66 captures the first monitoring image (with thelow quality), the operating processor 68 simply analyzes the firstmonitoring image for determining whether to actuate the external host64.

In one embodiment, the image capturing unit 66 captures the low qualitymonitoring image by using partial pixels, such as to divide the pixelarray into a plurality of 2×2 pixel blocks and to use only one pixel ineach pixel block to capture the image. In another embodiment, the imagecapturing unit 66 captures image by all pixels and divides all pixels toseveral pixel block (such as 2×2 pixel block) so as to combine values inall pixels in each pixel block as a block value and generates the lowquality monitoring image by those block values.

In step S210, the operating processor 68 preferably analyzes a specificregion of interest (ROI) within the first monitoring image to determineactuation of the external host 64, dimensions of the specific region issmaller than the first monitoring image, so that the operating processor68 can rapidly acquire an image analysis result due to less datacalculation in ROI; the first monitoring image setting as a low qualitymonitoring image is helpful to speedup image analysis about the specificregion of interest. Position and dimensions of ROI are preferablypre-defined by the user, for example, a door and a window are situatedin the first monitoring image, ROI can cover the pattern of the door toavoid the analysis result from being interfered by left shadow on thewindow, or ROI can cover edges of window for detecting a thief climbinginto the window and also preventing the analysis result from beinginterfered by the left shadow; the position and dimensions of ROIfurther may be varied according to the analysis result. However, theoperating processor 68 may analyze an entire region within the firstmonitoring image to perform the step S210, which depends on designdemand. The said image analysis can be executed by identifying a patterncontour within the monitoring image, comparing feature point on themonitoring image, and analyzing intensity variation of the monitoringimage optionally.

As the object does not conform to the predetermined condition, suck likethe passerby within the monitoring image being the animal instead of thehuman, step S212 is executed to not actuate the external host 64, andthe image capturing unit 66 may be passively or actively shut down toback the sleep mode. As the object conforms to the predeterminedcondition, which means the passerby within the monitoring image may bean unauthorized person, step S214 is executed to actuate the externalhost 64 and the image capturing unit 66 starts to capture the secondmonitoring image with the high quality, and the second monitoring imagecan be captured as static images format or a continuing video format andcan be stored inside the memory 70. Next, step S216 is executed that theexternal host 64 receives the second monitoring image and utilizes imagerecognition algorithm to precisely analyze the object within the secondmonitoring image.

The second monitoring image does not conform to a predeterminedthreshold, which means the object is not the unauthorized person, stepS218 is executed to shut down the motion detection device 60 passivelyor actively for energy economy; the second monitoring image conforms tothe predetermined threshold, hence the object is defined as theunauthorized person, step S220 is executed that the external host 64 canswitch the motion detection device 60 into the recording mode, themotion detection device 60 transmits the monitoring video outwardly forbackup, and the other motion detection devices 60′ can be simultaneouslyawaken for overall monitoring. Therefore, the passive detector 62 cannotdirectly actuate the external host 64 while detecting the object, themotion detection device 60 wakes up by trigger of the passive detector62 to capture the first monitoring image, and the external host 64 isactuated in accordance with the low quality image analysis of the firstmonitoring image through the motion detection device 60.

The motion detection device 60 can begin to capture the secondmonitoring image while the external host 64 is actuated. The externalhost 64 has to spend a period of time on waking other motion detectiondevices, the second monitoring image can record any doubtful eventinside the monitoring region before the other motion detection devicesare awaken, which means the monitoring system does not miss the doubtfulevent in a term between a detection timing of the passive detector 62and a wakeup timing of the other motion detection devices. The firstmonitoring image with the low quality is used by the motion detectiondevice 60 to determine existence of the object, the existencedetermination is rough computation and may be affected by noise, and thesecond monitoring image with the high quality is used by the externalhost 64 to analyze the accurate motion detection of the object, such asface recognition.

The present invention further provides an exposure adjustment functionfor preferred operational efficiency of the motion detection device 60.Please refer to FIG. 8 and FIG. 9 . FIG. 8 is a flow chart of a motiondetection method applied to the motion detection device 60 according toanother embodiment of the present invention. FIG. 9 is a waveformdiagram of a frame rate executed by the image capturing unit 66according to the foresaid embodiment of the present invention. In theembodiment, steps having the same numeral as one of the above-mentionedembodiment have the same content, and a detailed description is omittedherein for simplicity. As the motion detection device 60 is not awakenby the passive detector 62, step S205 can be executed to periodicallyswitch the image capturing unit 66 to the wakeup mode in the low framerate, and the image capturing unit 66 in the wakeup mode can execute theexposure adjustment and capture a low quality background image. As themotion detection device 60 is awaken, step S207 is executed to transformthe image capturing unit 66 into the wakeup mode in the high frame rate,and later, the image capturing unit 66 still captures the monitoringimage with the low quality to compare with the background image fordetermining actuation of the external host 64.

For example, as shown in FIG. 9 , the image capturing unit 66 mayexecute the exposure adjustment and capture the background image oneframe per second (1 fps) while the motion detection device 60 is nottriggered by the passive detector 62, which means an exposure parameterof the image capturing unit 66 can be adjusted and the background imagecan be established at timing T1, T2, T3 and T4. While the passivedetector 62 triggers the motion detection device 60 into the wakeup modeat timing T5, the motion detection device 60 may capture the firstmonitoring images thirty frames per second (30 fps), the latestbackground image (captured at the timing T4) has the exposure parametersimilar to ones of the first monitoring image captured at the timing T5,so that the image capturing unit 66 in the wakeup mode is not in need ofthe exposure adjustment, and can immediately acquire the superiormonitoring image with suitable exposure parameters.

In conclusion, the motion detection device of the present invention iselectrically connected between the passive detector and the externalhost, and the motion detection device is utilized to actuate theexternal host while the passive detector triggers the motion detectiondevice switched from the sleep mode to the wakeup mode. As the motiondetection device is in the sleep mode, the motion detection device canbe awaken in the low frame rate or stay in the sleep mode to adjust theexposure parameter and to capture the background image; as the motiondetection device is switched to the wakeup mode, the motion detectiondevice is transformed into the high frame rate to capture the lowquality monitoring image. The motion detection device executes thesimple image analysis via ROI of the low quality monitoring image for astart for determining whether to actuate the external host; since themotion detection device actuates the external host, the motion detectiondevice captures and stores the high quality monitoring image, and thehigh quality monitoring image can be used by the external host for theaccurate image analysis and execution of related application programs.The motion detection device of the present invention can effectivelyeconomize start-up time of the monitoring system without waiting for awakeup period of the external host and an exposure adjustment period ofthe motion detection device.

Please refer to FIG. 10 and FIG. 11 . FIG. 10 is a functional blockdiagram of a smart motion detection device 80 according to a firstembodiment of the present invention. FIG. 11 is a procedural diagram ofthe smart motion detection device 80 according to the first embodimentof the present invention. The smart motion detection device 80 caninclude a memory 82, a processor 84 and a sensor array 86, which arethree separate components or combined as one or two integratedcomponents. The sensor array 86 can be directly coupled to the memory 82and further electrically connected with the processor 84. The sensorarray 86 includes a plurality of light detecting pixels arranged intwo-dimension manner to capture images. The processor 84 can be switchedbetween a sleep mode and a wakeup mode, and used to process an imagecaptured by the sensor array 86 to identify a particular event in thecaptured images, such as an unexpected object been captured in thecaptured images.

The image captured by the sensor array 86 may be pre-stored (i.e.,wrote) into the memory 82 or directly transmitted to the processor 84 inaccordance with modes of the processor 84 or an alarm signal resultedfrom motion detection. The memory 82 can have the image capacity ofpredefined quantity; when the memory 82 is full and a new image isprepared to pre-store, a former image can be removed for storing the newimage. The image processed by the processor 84 and the pre-stored imagein the memory 82 can be transmitted to an external storage module 88electrically connected with the smart motion detection device 80.

As the first embodiment shown in FIG. 11 , the processor 84 stays in thesleep mode when the smart motion detection device 80 is not activated.The sensor array 86 can include a comparator 90 adapted to generate thealarm signal when monitoring motion of an object. As the processor 84 isoperated in the sleep mode, the sensor array 86 continuously orintermittently captures a plurality of images (such as capture fiveimages in every 1 second), and the plurality of images are pre-storedinto the memory 82; in the meantime, the comparator 90 reads andcompares at least some of the pre-stored images I1 with a referenceimage. When intensity variation between one of the pre-stored images I1and the reference image is smaller than a predefined value, theprocessor 84 keeps in the sleep mode and the comparator 90 reads thenext pre-stored image I1 for a comparison with the reference image. Whenthe intensity variation is greater than the predefined value, thecomparator 90 can generate the alarm signal utilized to awake theprocessor 84 and further to pre-store the image captured by the sensorarray 86 into the memory 82. That is, the alarm signal is used to switchthe processor 84 from the sleep mode to the wakeup mode.

There has variety ways for the comparator 90 to compare the pre-storedimages I1 and the reference image, for example the comparator 90 couldcompare whole image range or only compare partial pixels for thepre-stored images I1 and the reference image. The comparator 90 couldcompare intensity summation of all pixels or partial pixels, in anotherway the comparator 90 could compare intensity of each pixel in wholeimage range or only partial pixels.

When the processor 84 is operated in the wakeup mode, a real-time imageI2 captured by the sensor array 86 is directly transmitted to theprocessor 84 for digital processing and may not be stored into thememory 82. The processor 84 in the wakeup mode may process the real-timeimage I2 and receive the pre-stored image I1 in the memory 82 by turns,or may receive the pre-stored image I1 after processing of the real-timeimage I2. A process of the real-time image I2 can precede that of thepre-stored image I1, so the smart motion detection device 80 is able tofocus on an instant situation within the monitoring area. The process ofthe pre-stored image I1 may be executed when the process of thereal-time image I2 is completed or paused. If an operating capability ofthe processor 84 is sufficient for mass data, the real-time image I2 andthe pre-stored image I1 can be processed alternately, hence the smartmotion detection device 80 can show detection results about the currentand previous period at the same time.

In some embodiments, the pre-stored images captured by the sensor array86 when the processor 84 is operated in the sleep mode can be pre-storedinto the memory 82, and the real-time images captured by the sensorarray 86 when the processor 84 is operated in the wakeup mode can betransmitted to the processor 84. In other embodiments, the processor 84and the sensor array 86 can be turned off under a non-working mode; whenthe smart motion detection device 80 receives a trigger signal, thesensor array 86 can capture and send the images to the memory 82directly, and then the processor 84 can send a request to the sensorarray 86 for receiving the captured images. The trigger signal may be analarm resulted from an external unit or a built-in unit of the smartmotion detection device 80.

In addition, at least one of an image quality and a frame rate of thesensor array 86 may be changed when the processor 84 is operated in thesleep mode or the wakeup mode. For example, as the processor is in thesleep mode, the sensor array 86 can capture the low-quality image orcapture the image in the low frame rate for comparing with the referenceimage. Transmission bandwidth and storage capability are economizedaccordingly. The alarm signal is generated because the intensityvariation between the low-quality image (or the image captured in thelow frame rate) and the reference image is greater than the predefinedvalue, so that the sensor array 86 starts to capture the high-qualityimage or capture the image in the high frame rate for pre-storing intothe memory 82, and simultaneously the processor 84 can be switched tothe wakeup mode. Then, the pre-stored high-quality image or thepre-stored image captured in the high frame rate in the memory 82 istransmitted to the processor 84 operated in the wakeup mode; thereforethe smart motion detection device 80 does not lose image informationbefore the processor 84 is in the wakeup mode.

Please refer to FIG. 12 to FIG. 15 . FIG. 12 is a functional diagram ofthe smart motion detection device 80′ according to a second embodimentof the present invention. FIG. 13 is a procedural diagram of the smartmotion detection device 80′ according to the second embodiment of thepresent invention. FIG. 14 is a functional diagram of the smart motiondetection device 80″ according to a third embodiment of the presentinvention. FIG. 15 is a procedural diagram of the smart motion detectiondevice 80″ according to the third embodiment of the present invention.In the embodiments, elements having the same numerals as ones of thefirst embodiment have the same functions, and a detailed description isomitted herein for simplicity.

In a possible embodiment, the smart motion detection device 80′ caninclude the memory 82, the processor 84, the sensor array 86′ and apassive sensor 92. The passive sensor 92 is electrically connected withthe processor 84 and the sensor array 86′. The processor 84 is kept inthe sleep mode and the sensor array 86′ is shut down when the passivesensor 92 does not detect any abnormal situation. As the passive sensor92 detects the motion of the object, the passive sensor 92 can generatethe alarm signal, and the alarm signal is used to drive the sensor array86′ and switch the processor 84 from the sleep mode to the wakeup mode.When the processor 84 is still in the sleep mode, the sensor array 86′can capture and transmit the pre-stored image I1 to the memory 82. Whenthe processor 84 is operated in the wakeup mode, the sensor array 86′can capture and transmit the real-time image I2 to the processor 84, andthe pre-stored image I1 in the memory 82 can be transmitted to theprocessor 84 accordingly.

The smart motion detection device 80 may have the non-working mode. Theprocessor 84 and the sensor array 86′ can be turned off under thenon-working mode. As the passive sensor 92 detects the motion of theobject and generates the alarm signal, the sensor array 86′ is triggeredby the alarm signal and starts to capture and send the pre-stored imageinto the memory 82. After that, the processor 84 can be switched to thewakeup mode and then sends the request to the sensor array 86′ forreceiving the pre-stored image.

In another possible embodiment, the smart motion detection device 80″can include the memory 82, the processor 84, the sensor array 86″ havingthe comparator 90, and the passive sensor 92. The passive sensor 92 canactivate the sensor array 86″ when detecting the abnormal situation. Theactivated sensor array 86″ can capture and transmit the pre-stored imageI1 to the memory 82, and the comparator 90 can compare the pre-storedimage I1 with the reference image for determining whether to switch onthe processor 84. The comparator 90 is utilized to identify the abnormalsituation. If the intensity variation between the pre-stored image I1and the reference image is smaller than the predefined value, theabnormal situation may be resulted from noise and the processor 84 isnot switched on. If the intensity variation is greater than thepredefined value, the abnormal situation can be defined as someone orsomething intruding into the monitoring area of the smart motiondetection device, so that the processor 84 is switched to the wakeupmode for recording. As the processor 84 is operated in the wakeup mode,the real-time image I2 captured by the sensor array 86″ and thepre-stored image I1 in the memory 82 can be transmitted to the processor84 and then to the external storage module 88 for the digitalprocessing.

Please refer to FIG. 16 . FIG. 16 is a flow char of a determining methodaccording to the embodiment of the present invention. The determiningmethod illustrated in FIG. 16 can be suitable for the smart motiondetection devices shown in FIG. 10 to FIG. 15 . First, steps S800 andS802 are executed to start the determining method and to monitor themotion of the object. The said monitoring function can be applied by thesensor array 86, 86′ and 86″ or the passive sensor 92. As there is notabnormal situation, step S804 is executed to keep the processor 84 inthe sleep mode; as the motion of the object is detected, steps S806 andS808 are executed to generate the alarm signal for enabling theprocessor 84 and capturing the image via the sensor array 86, 86′ and86″. When the processor 84 is not operated in the wakeup mode, step S810is executed that the sensor array 86, 86′ or 86″ can produce thepre-stored image I1 in the memory 82. When the processor 84 is operatedin the wakeup mode, steps S812 and S814 are executed that the sensorarray 86, 86′ or 86″ can produce the real-time image I2, and both thepre-stored image I1 and the real-time image I2 can be transmitted to theprocessor 84.

After that, step S816 is executed that the processor 84 can analyze thereal-time image I2 captured by the sensor array 86, 86′ or 86″ whencapturing function of the sensor array 86, 86′ or 86″ is activated. Whenthe sensor array 86, 86′ or 86″ is not activated, probably owning to thedisappeared object or any other situations, step S818 is executed toanalyze the pre-stored image I1 inside the memory 82 by the processor84. It should be mentioned that the processor 84 not only can processthe real-time image I2 before the pre-stored image I1, but alsoalternately process the pre-stored image I1 and real-time image I2 inaccordance with the user's actual demand and the sufficient operatingcapability.

In conclusion, the alarm signal may be generated by the sensor array orthe passive sensor (which can be a thermal sensor, an accelerometer or agyro). The alarm signal is utilized to activate pre-storing operation ofthe sensor array and mode switching operation of the processor. When thealarm signal is received, the sensor array can be activated to capturethe pre-stored image at a first time and the pre-stored image istransmitted to the memory. For waiting a duration of the processorswitched from the sleep mode to the wakeup mode, the processor whichreceives the alarm signal can send a request to the sensor array for thereal-time image and the pre-stored image at a second time later than thefirst time, so that the pre-stored image from the memory are processedlater than the first time, and the real-time image is not stored intothe memory but directly transmitted to the processor for the digitalprocessing. Comparing to the prior art, the smart motion detectiondevice and the related determining method of the present invention caneffectively economize start-up time of the smart motion detection devicewithout waiting for a wakeup period of the processor.

FIG. 17 is a block diagram of an image sensor device 1700 applied into asecurity monitoring system according to an embodiment of the invention.The image sensor device 1700 is capable of generating one or moremonitoring images, providing one or more regions of interest (ROIs) onone or more monitoring images, determining an alarm schedule of ROIs,and automatically generating a ranking list of ROIs and alarm videos fora user based on the priority levels of one or more ROIs. The prioritylevels can be automatically determined by the image sensor device 1700after a period of usage time of the image sensor device 1700. An ROI maybe also referred to as a window of interest (WOI); this is not intendedto be a limitation. The image sensor device 1700 can be coupled to abackend system 1701 such as a computer device via wired or wirelesscommunications, and the backend system 1701 can be arranged forautomatically displaying related monitoring images for the user or canbe operated by the user to display corresponding monitoring images. Theimage sensor device 1700 is arranged to transmit the ranking list of theROIs and corresponding monitoring images to the backend system 1701, andthe backend system 1701 can display the suggested ranking list of theROIs so that the user can view monitoring images of specific ROI(s)sooner.

It should be noted that the operation of determining the alarm scheduleof ROIs for the user may comprise outputting alarm video/image(s) ofonly one ROI real-timely or later, outputting alarm video/images ofmultiple ROIs real-timely or later, and/or arranging the output scheduleof alarm video/images of multiple ROIs. Such operation is performedbased on the priority levels of ROIs. For example, the alarmvideo/images of multiple ROIs can be scheduled to be outputted for theuser periodically (e.g. every night or every weekend (not limited))based on the priority levels of ROIs. It should be noted that, the alarmvideo/image(s) of only one ROI can be scheduled to be outputted for theuser periodically (e.g. every night or every weekend (not limited))based on the priority level of such ROI. For instance (but not limited),if the priority level of such ROI is urgent or important, the alarmvideo/image(s) of such ROI can be scheduled to be outputted for the userevery night. Instead, if the priority level of such ROI is not urgent orunimportant, the alarm video/image(s) of such ROI may be scheduled to beoutputted for the user every weekend.

The image sensor device 1700 can be configured or installed within asurveillance camera device or a security camera device of the securitymonitoring system, and the surveillance camera device, which comprisingthe image sensor device 1700 having the capability of automaticallygenerating the ranking list of ROIs for the user, can be freely set atany locations or any positions or with any angles by the user.

The image sensor device 1700 automatically generates the ranking list ofROIs, in which an ROI having the higher priority level is ranked in thefront of another ROI having the lower priority level, for the user, sothat the user can view the images/videos of the ROI having the higherpriority level at first or sooner and then view the images/videos of theROI having the lower priority level if it is needed. By doing so, it ismore efficient for the user to determine whether a specific/true motionevent actually occurs, and also it is not needed for the user tomanually adjust the location/position of the surveillance camera deviceto avoid undesired/unwanted image fluctuations. In other embodiments,images/videos corresponding to an ROI having a much lower priority levelmay be not displayed for the user to avoid meaninglessinterruptions/warnings for the user.

Refer to FIG. 18 . FIG. 18 is a diagram showing an example of ROIs on amonitoring image according to an embodiment of the invention. As shownin FIG. 18 , the monitoring image at least comprises an outdoor imageportion such as images of shaking leaves within the ROI R1 and an indoorimage portion such as a human-shape image within the ROI R2. In thisexample, the motions of shaking leaves are undesired/unwanted imagefluctuations, and the processing circuit 1710 for example can bearranged to rank the priority level of the ROI R2 at the front of thatof ROI R1 based on the features of the images of shaking leaves andfeatures of the human-shape image to make the user view the human-shapeimage sooner. It should be noted that the shapes and sizes of differentROIs can be identical or can be different.

Refer to FIG. 17 again. In practice, the image sensor device 1700comprises a sensing circuit 1705 and a processing circuit 1710. Thesensing circuit 1705 is used for generating one or more monitoringimages and for providing a plurality of regions of interest (ROIs) onthe monitoring image(s). That is, the sensing circuit 1705 captures aplurality of monitoring images through the image sensor device 1700, andit generates a plurality of regions of interest (ROIs) for each of theplurality of monitoring images. For example (but not limited), thesensing circuit 1705 when being enabled is arranged to continuouslycapture images to generate monitoring images, and the ROIs are spatialregions respectively located on each monitoring image. The processingcircuit 1710 is coupled to the sensing circuit 1705. For one or eachROI, the processing circuit 1710 is configured for detecting whether atleast one motion event occurs within the one or each ROI and determininga priority level of the one or each ROI according to at least onefeature information of the at least one motion event. After generatingthe priority levels of the ROIs, the processing circuit 1710 is arrangedfor automatically generating and outputting a ranking list of the ROIsfor a user according to the priority levels of the ROIs.

FIG. 19 is a flowchart diagram of a method of the image sensor device1700 of FIG. 17 according to an embodiment of the invention. Thedescription of steps is simply described in the following:

Step S1900: start;

Step S1905: sensing circuit 1705 generates monitoring images andprovides ROIs;

Step S1910: processing circuit 1710 detects motion event(s) within eachROI;

Step S1915: processing circuit 1710 detects feature(s) of motionevent(s) within each ROI;

Step S1920: processing circuit 1710 classifies each motion event intoone or more categories/types according to the feature(s) of each motionevent for each ROI;

Step S1925: processing circuit 1710 determines the priority level ofeach ROI according to the number (s) of one or more classifiedcategories of each ROI;

Step S1930: processing circuit 1710 generates the ranking list of ROIsaccording to the priority levels of the ROIs; and

Step S1935: End

Actually, an object (or motion object) may occur at a spatial positionin a monitoring image, keep still or move slowly or fast, and finallymay disappear at the same or a different position in another monitoringimage. According to the monitoring images generated from the sensingcircuit 1705, the processing circuit 1710 of FIG. 17 can detect anddetermine that the motion object occurs in a monitoring image anddisappears in another monitoring image. Identically, based on themonitoring images, for a specific ROI or each ROI, the processingcircuit 1710 can detect and determine that a motion object occurs in theROI at a timestamp associated with a monitoring image and disappears inthe ROI at another timestamp associated with another monitoring image,to generate a motion event for the ROI. Similarly, for the ROI, theprocessing circuit 1710 can detect and determine that different motionobjects occur in the ROI at identical or different timestamps anddisappear in the ROI at identical or different timestamps, to generatemultiple different motion events for the ROI. Different ROIs may beassociated with the motion events having identical, partially identical,or different features.

For example, if a motion object moves from an ROI to another ROI on themonitoring images, then the processing circuit 1710 generates two motionevents, associated with the same motion object, individually for the twoROIs, and the features of the two motion events of the two ROIs in thissituation may be identical (or may be partially identical since thetimestamp information is different). Instead, if two different motionobjects respectively occurs and disappears in different ROIs, then theprocessing circuit 1710 generates two motion events, associated with thedifferent motion objects, individually for the two ROIs, and thefeatures of the two motion events of the two ROIs in this situation aredifferent (or may be partially different since some information such ascolor, shape, or timestamp information may be identical).

In practice, for one or each ROI, the processing circuit 1710 maycompare one or more feature information of the one or more detectedmotion objects/events with candidate feature information, which may bepre-recorded in the memory circuit of the processing circuit 1710, togenerate the feature information of the motion events occurring the oneor each ROI. For example, at least one feature information of at leastone motion event comprises at least one of the following features: atime of appearance/occurrence, a time which the at least one motionevent disappears, a time length between the at least one motion event'soccurring and disappearing, a frequency which the at least one motionevent occurs, a regularity level which the at least one motion eventoccurs, at least one timestamp of the at least one motion event, ashape/color/size of at least one motion object in the at least onemotion event, and a motion direction/speed of the at least one motionobject, etc. Other feature information of motion objects may be includedwithin and used as the feature information, and the examples of theabove-mentioned feature information are not intended to be limitations.Similarly, the above-mentioned candidate feature information alsocomprises at least one of the above similar feature information.

After a period of usage time, the processing circuit 1710 can generateand record all the feature information of the motion events of the ROIsin a memory circuit (not shown in FIG. 17 ) of the processing circuit1710. Then, the processing circuit 1710 can automatically generate andoutput the ranking list of the ROIs for the user according to the user'spreferred settings or a default setting, so that the user can easilyview important monitoring images within an ROI and ignore unimportantmonitoring images within another ROI; the ROI having the most importantmonitoring images can be ranked first to make the user easily view theimages of such ROI, and the importance can be determined by theprocessing circuit 1710 based on the user's preferred settings or thedefault setting.

In the embodiment, for example, for a specific or each ROI, theprocessing circuit 1710 can be arranged to classify multiple motionevents having identical/similar features into a same category andclassify motion events having different features into differentcategories. One motion event may be associated with one or morecategories.

For example, in one embodiment, motion events having motion objectsassociated with identical/similar shapes/sizes may be classified intothe same shape/size category, and motion events having motion objectsassociated with different/dissimilar shapes/sizes may be classified intodifferent shape/size categories. For instance (but not limited), motionevents of shaking leaves (or shaking grass) may be classified into thesame leaf/grass category, motion events associated with human-shapemotion objects may be classified into a different human-shape category,and motion events associated with vehicle-shape objects may beclassified into another different vehicle-shape category. These examplesare not intended to be limitations.

Further, in another embodiment, motion events having motion objectsassociated with identical/similar colors may be classified into the samecategory, and motion events having motion objects associated withdifferent/dissimilar colors may be classified into different categories.For instance (but not limited), motion events corresponding to shakingleaves and motion events corresponding to shaking grass may beclassified into the same green color category, and the motion eventsassociated with human-shape motion objects may be classified into adifferent color category.

Further, in another embodiment, motion events corresponding to higherfrequency motions and motion events corresponding to lower frequencymotions may be classified into different categories respectively. Forinstance (but not limited), motion events corresponding to shakingleaves and motion events (high frequency motions) may be classified intothe same high-frequency category, and the motion events associated withhuman motion objects (low frequency motions) may be classified into adifferent low-frequency category.

Further, in another embodiment, motion events corresponding to higherregularity motions and motion events corresponding to lower regularitymotions may be classified into a different category respectively. Forinstance (but not limited), motion events corresponding to shakingleaves, shaking grasses, or the place/time which people usually come andgo may be classified into the same high-regularity category since themotion events are associated with higher regularity level, and themotion events corresponding to motion objects occurring in theplace/time which people rarely come and go may be classified into adifferent low-regularity category since the motion events are associatedwith lower regularity level.

Further, in another embodiment, motion events corresponding to differenttime periods such as morning session(s), noon session(s), afternoonsession(s), night session(s), working hours, off-hours, and etc. may beclassified into different categories respectively. For instance (but notlimited), motion events corresponding to working hours may be classifiedinto the same working-hours category, and the motion eventscorresponding to off-hours may be classified into a different off-hourscategory.

Similarly, motion events corresponding to different times ofappearance/occurrence/disappearing, different time lengths betweenoccurring and disappearing, different timestamps, and/or differentmotion directions/speeds are respectively classified into differentcategories, and motion events corresponding to the same/similar featuresare classified into the same category.

It should be noted that the processing circuit 1710 is capable ofclassify one motion event into multiple categories in accordance with atleast one of the above-mentioned feature information. For instance, amotion event corresponding to a motion object occurring in the placewhich people rarely come and go during off-hours for a specific timelength may be classified and have three different categories whichrespectively indicate that the motion object occurs in the place whichpeople rarely come and go, the motion object occurs during theoff-hours, and indicate the motion object occurs for the specific timelength. This example is not meant to be a limitation of the invention.

Based on the classified categories of the different ROIs, the processingcircuit 1710 then is arranged to grade the different ROIs by givingdifferent scores to the different categories so as to generate thepriority levels of the different ROIs. For example (but not limited),for security monitoring, a leaf-shape (or grass-shape) categorycorresponds to a lower score while a human-shape category or avehicle-shape category corresponds to a higher score; a green colorcategory corresponds to a lower score while a different color categorycorresponds to a higher score; a high-frequency category corresponds toa lower score while a low-frequency category corresponds to a higherscore; a high-regularity category corresponds to a lower score while alow-regularity category corresponds to a higher score; a working-hourscategory corresponds to a lower score while an off-hours categorycorresponds to a higher score; the examples are not intended to belimitations of the invention. Other modification examples are alsosuitable.

After giving scores to the categories of the different ROIs, theprocessing circuit 1710 is arranged to calculate the sum or average (orweighted average) of all scores of each ROI and then to determine thepriority levels of the different ROIs based on the sum or average ofscores of each ROI wherein a higher sum or average corresponds to ahigher priority level. For example, the priority level of a first ROI,which is associated with a motion event corresponding to a motion objectoccurring in the place which people rarely come and go during off-hourswith a lower regularity level, may be ranked near the top (or for thefirst one) of the ranking list, and the priority level of a second ROI,which is associated with another motion event corresponding to anothermotion object such as shaking leaves with a higher regularity level, maybe ranked near the bottom or the last one of the ranking list. By doingso, once a user receives the ranking list, the user can view themonitoring images within the first ROI to see the images of suchimportant motion event by eyes sooner and ignore the images of thesecond ROI.

In another embodiment, the image sensor device 1700 is capable ofproviding a feedback control operation which can receive the user'srequest/feedback control to real-timely or dynamically adjust thepriority level(s) of one or more ROIs. FIG. 20 is a block diagram of theimage sensor device 1700 applied into the security monitoring systemaccording to another embodiment of the invention. In this embodiment,the processing circuit 1710 is arranged to tag unique identification(ID) information for each motion event within each ROI. When a motionevent is detected by the processing circuit 1710, the processing circuit1710 transmits the image stream associated with such motion event andthe tagged ID information to the backend system 1701, and this tagged IDinformation can be used as an alarm ID of such motion event. The backendsystem 1701 generates the alarm video, which comprises the image streamsand alarm ID, for the user.

The user can adjust the priority level of an ROI corresponding to suchmotion event or adjust the priority of such motion event by operatingthe backend system 1701 to generate a feedback control to the backendsystem 1701 or by using a mobile device to generate a feedback controlsignal to the backend system 1701. The backend system 1701 transmits theadjusted priority information and the alarm ID to the image sensordevice 1700, and the processing circuit 1710 can adjust up or adjustdown the priority level of the ROI corresponding to such motion event oradjust the priority of such motion event. For example, in a scenario, ifthe motion event and alarm video are associated with shaking leaves (butnot limited), i.e. the motion event and alarm video which the user wouldlike to ignore, the user may press/click/touch a dislike icon for thealarm video, and the processing circuit 1710 can adjust down thepriority level of a specific ROI corresponding to the alarm video basedon the motion event's ID information which is associated with thereceived alarm ID information corresponding to the alarm video.Alternatively, in another scenario, a motion event and alarm video maybe associated with a human-shape motion object (but not limited), i.e.the motion event and alarm video which the user can press/click/touch alike icon for the alarm video, and the processing circuit 1710 canadjust up or keep the priority level of a specific ROI corresponding tothe alarm video based on the motion event's ID information which isassociated with the received alarm ID information corresponding to thealarm video. Thus, by doing so, the ranking list of the ROIs can bedynamically or real-timely updated for the user based on the user'sfeedback control/behavior. That is, the processing circuit 1710 canreceives the user's feedback in favor of at least one ROI and select atleast one ROI in a higher/highest priority level to be displayed to theuser.

Additionally, the processing circuit 1710 is arranged to assigndifferent ID information for multiple motion events having one or moreidentical features. For example, a motion event of shaking leaves and amotion event of shaking grass are assigned two different unique IDsrespectively wherein the shaking leaves and shaking grass at leastinclude identical features of green color. Then the processing circuit1710 classifies the motion events having one or more identical featuresinto a same event group (i.e. a same category). Then, in response to theuser's adjustment setting for a particular motion event in the motionevents, the processing circuit 1710 can determine or identify one ormore ROIs which are associated with the motion events belonging to thesame event group (or the same category) based on the different IDs.Then, the processing circuit 1710 can adjust one or more priority levelsof the one or more ROIs according to the same/identical adjustment ofthe user which made for the particular motion event in a specific ROI.That is, if the user would like to adjust the priority of a specificmotion event, the processing circuit 1710 can determine which motionevent(s) and which ROI(s) are associated with the category of thespecific motion event based on the different IDs, and then it can adjustthe priority level(s) of the determined ROI(s) based on the sameadjustment made for the specific motion event.

Further, in other embodiments, the image sensor device 1700 or thesecurity monitoring system may comprise different notification modes.The processing circuit 1710 can employ different notification modesbased on the different priority levels of the ROIs and transmitdifferent notifications of alarm videos associated with the differentROIs to the user according to the different notification modes. Theprocessing circuit 1710 may transmit a first notification to the user tonotify the user of a first motion event occurring within a first ROIaccording to a first notification mode, and it may transmit a secondnotification to the user to notify the user of a second motion eventoccurring within a second ROI according to a second notification mode.The first notification mode is more urgent than the second notificationmode when a priority level of the first ROI is higher than a prioritylevel of the second ROI. Also, the priority levels can be dynamically orreal-timely adjusted based on the user's adjustment or request. Forexample, the processing circuit 1710 may instantly transmit anotification for the user according to an instant notification mode ifthe processing circuit 1710 detects a motion event occurring within aspecific ROI. A user may press/click/touch a dislike icon for the alarmvideo of such motion event to send a feedback control signal to thebackend system 1701, and the processing circuit 1710 can lower thepriority level of the specific ROI according to the feedback controlsignal transferred from the backend system 1701 and may use a laternotification mode to notify the user if an identical/similar motionevent occurs in the specific ROI again. The later notification mode maymean that the notification is generated after waiting for a time periodsuch as minutes, hours, days, or etc. Alternatively, the laternotification mode may indicate that the processing circuit 1710 cangenerate a summary report, which is associated with theidentical/similar/different features of all motion events in thespecific ROI, for the user after waiting for the time period.Alternatively, the processing circuit 1710 may determine not notifyingthe user when an identical/similar motion event occurs in the specificROI again if the user repeatedly presses/clicks/touches the dislike iconfor an alarm video of the identical/similar motion event.

Additionally, in other embodiments, different image streams of motionevents detected by different image sensor devices can be merged orcombined to generate and provide a merged image stream for the user.Refer to FIG. 21 . FIG. 21 is a diagram of an example of multiple imagesensor devices 1700A, 1700B, 1700C respectively comprised by orinstalled within different camera devices being disposed at differentlocations in a security monitoring system according to an embodiment ofthe invention. It should be noted FIG. 21 shows three image sensordevices; however, this is not intended to be a limitation. The number ofimage sensor devices can be equal to or more than two. In addition, thelocations at which the image sensor devices disposed are also notlimited. As shown in FIG. 21 , the multiple image sensor devices 1700A,1700B, 1700C are arranged to capture monitoring images at differentlocations based on different field of views A1, A2, A3 so as to generatemultiple image streams. In this embodiment, the image sensor devices1700A, 1700B, 1700C respectively comprise the corresponding sensingcircuits 1705A, 1702B, 1705C and processing circuits 1710A, 1710B,1710C, and the basic functions and operations of circuits 1705A, 1705B,1705C and 1710A, 1710B, 1710C are respectively similar to those ofcircuits 1705 and 1710 mentioned above. In addition, the backend system1701 further comprises a system storage 1702 which may be implemented byusing a memory circuit and used for storing image streams, motionevents, corresponding timestamps, and corresponding IDs.

For example, in one embodiment, a motion object such as a human-shapeobject (but not limited) may occur in the field of views of the imagesensor devices 1700A, 1700B, 1700C, sequentially. That is, the imagesensor devices 1700A, 1700B, 1700C may sequentially usedifferent/identical ROIs to capture the image streams corresponding tothe motion object.

For instance, the processing circuit 1710A may detect a motion event EA,which is associated with the human-shape motion object, within an ROI RAon monitoring images generated from the sensing circuit 1705A, and theprocessing circuit 1710A is arranged to identify and generate thefeature information of the motion event EA and also tag a timestamp tAand unique ID ID_A to the motion event EA. Then, the processing circuit1710A transmits and outputs the motion event EA, image streams of motionevent EA, timestamp tA, and the ID ID_A to the backend system 1701, andthe backend system 1701 stores such information into the system storage1702.

Later, the processing circuit 1710B may detect a motion event EB, whichis also associated with the same human-shape motion object, within anROI RB on monitoring images generated from the sensing circuit 1705B,and the processing circuit 1710B is arranged to identify and generatethe feature information of the motion event EB and tag a timestamp tB tothe motion event EA. In this situation, the processing circuit 1710B isarranged to transmit a request signal to the backend system 1701 to makethe backend system 1701 search the space of the system storage 1702according to the generated feature information of motion event EB andthe timestamp tB. The backend system 1701 can compare the featureinformation of motion event EB (and/or the timestamp tB) with the storedfeature information such as feature information of motion event EA(and/or stored timestamp such as timestamp tA) to check whether thefeatures are identical or similar and/or check whether the timestampsare adjacent or close.

In this example, the features of motion events EA and EB areidentical/similar and the corresponding timestamps are adjacent, and thebackend system 1701 is arranged to transmit the ID of the previousmotion event EA to the processing circuit 1710B. If the features are notidentical/similar and the corresponding timestamps are notadjacent/close, then the backend system 1701 is arranged to not transmitthe ID ID_A of the previous motion event EA and notify the processingcircuit 1710B of using a new unique ID. After receiving the ID ID_A ofthe motion event EA, the processing circuit 1710B uses ID ID_A as the IDof the motion event EB, tags the ID ID_A into the image streams of themotion event EB, and outputs the image streams of motion event EB to thebackend system 1710.

Similarly, for the image sensor device 1700C, the processing circuit1710C may tag the ID ID_A into image streams of a detected motion eventEC and then transmit the image streams with the ID ID_A to the backendsystem 1701 if the feature of motion event EC is identical/similar tothat of motion event EA/EB and/or timestamp tC is adjacent to timestampEA/EB. Finally, the backend system 1701 can merge or combine the motionevents' image streams having the same/similar features according to theorder or sequence of the timestamps, to generate a merged image streamas an alarm video for the user. For example, the merged image streamcomprise the image stream of motion event EA which is followed by theimage stream of motion event EB which is followed by the image stream ofmotion event EC if the timestamp tC is later than the timestamp tB whichis later than the timestamp tA.

By doing so, the user can directly view the alarm video which comprisesa full or complete movement history of the human-shape motion objectpassing through the places at which the image sensor devices 1700A,1700B, and 1700C are disposed. It is more convenient for the user sincethe user does not need to manually check different camera devices.

In addition, in another embodiment, each of the processing circuits1710A, 1710B, 1710C is capable of merging the image streams if it isneeded. For example, the system storage 1702 can be inside or outsidethe backend system and is coupled to the image sensor devices 1700A,1700B, 1700C via wired/wireless communications. In the above example ofthe human-shape motion object, the processing circuit such as 1710B isable to search the space of system storage 1702 according to thegenerated feature information of motion event EB and the timestamp tB,to compare the feature information of motion event EB (and/or thetimestamp tB) with the stored feature information such as featureinformation of motion event EA (and/or stored timestamp such astimestamp tA) to check whether the features are identical or similarand/or check whether the timestamps are adjacent or close. In thissituation, the features of motion events EA and EB are identical/similarand the corresponding timestamps are adjacent, and the processingcircuit 1710B uses the ID ID_A of motion event EA as the ID of motionevent EB (i.e. tags the ID ID_A into the motion event EB) so that theimage streams of motion events EA and EB are equivalently merged and thecorresponding timestamps tA and tB are also merged due to the same IDID_A.

Instead, if the features are not identical/similar and the correspondingtimestamps are not adjacent/close, then the processing circuit 1710Buses a unique and new ID, different from the ID ID_A, as the ID ofmotion event EB, and the image streams are not merged since of thedifferent IDs.

Similarly, in the example, the processing circuit 1710C later uses theID ID_A of motion event EA as the ID of motion event EC (i.e. tags theID ID_A into the motion event EC) so that the image streams of motionevents EA, EB, and EC are equivalently merged and the correspondingtimestamps tA, tB, and tC are also merged since of the same ID ID_A.Then, the backend system 1701 can directly output the alarm video, whichcomprises the image streams of motion events EA, EB, and EC, for theuser according to the order or sequence of the timestamps tA, tB, and tCand the same ID ID_A of the motion events EA, EB, and EC.

By doing so, once the user sends a user request to the backend system1701 to ask the monitoring images of a specific camera device disposedat a specific location, the backend system 1701 can automatically outputother image streams of other different camera devices, associated withthe same/similar features and/or adjacent timestamps, for the user, inaddition to outputting the image streams of the specific camera device.The other different camera devices may be spatially neighboring or canbe disposed in other different locations/buildings. That is, the imagesensor devices 1700A, 1700B, 1700C can generate and output at least oneimage of a first motion event and at least one image of a second motionevent for the user in response to the user request which asks the secondmotion event if the ID of the first motion event is identical to the IDof the second motion event.

It should be noted that each processing circuit can be arranged tocompare the timestamps to determine whether the timestamps are adjacentor close. For example, the processing circuit may determine that asecond timestamp is adjacent or close to a first timestamp if the secondtimestamp is followed by N timestamps which is followed by the firsttimestamp wherein the value of N may range from zero to a thresholdvalue. That is, if two timestamps are separated by more than Nconsecutive timestamps, then the two timestamps are not adjacent;otherwise, the two timestamps are adjacent. However, this exampledefinition is not meant to be a limitation of the invention.

In addition, if a timestamp of a second motion event is previous to atimestamp of a first motion event and the two motion events areassociated with the same/similar features, then the processing circuit1710A, 1710B, or 1710C may determine that the first motion event is nextto the second motion event which is obtained from the system storage1702.

Further, in one embodiment, the backend system 1701 or each of the imagesensor devices 1700A, 1700B, 1700C is able to store a relation betweenmultiple image sensor devices if the motion events generated from theimage sensor devices are associated with the same/similar featuresand/or adjacent timestamps. For instance, in the above example, theimage sensor devices 1700A, 1700B, 1700C may respectively andsequentially detects motion events EA, EB, EC which are all associatedwith the same motion object such as a human-shape motion object passingthrough the locations at which the image sensor devices 1700A, 1700B,1700C are disposed. The motion events EA, EB, EC are associated with thesame/similar features and adjacent timestamps, and the timestamp tC islater than the timestamp tB that is later than the timestamp tA.

For the image sensor device 1700B, when detecting the motion event EB,the processing circuit 1710B can compare the features and timestamps ofthe motion events EB and EA and then determine that the features areidentical/similar and the timestamps are adjacent. In this situation, inaddition to using the ID of the motion event EA as the ID of the motionevent EB, the processing circuit 1710B further generates a relation dataRD1 of the devices 1700A and 1700B to indicate that the devices have arelation wherein the relation data RD1 corresponds to the same ID ofmotion events EA and EB. Such relation data RD1 is transmitted to theimage sensor device 1700A so that each of the image sensor devices 1700Aand 1700B stores the relation data RD1 corresponding to the same ID.

Then, for the image sensor device 1700C, when detecting the motion eventEC, the processing circuit 1710C can compare the features and timestampsof the motion events EC and EB (or EA) and then determine that thefeatures are identical/similar and the timestamps are adjacent. In thissituation, in addition to using the ID of the motion event EA (i.e. theID of motion event EB since the ID is identical) as the ID of the motionevent EC, the processing circuit 1710C further generates anotherrelation data RD2 of the devices 1700A, 1700B, and 1700C to indicatethat the three devices have a relation wherein the another relation dataRD2 corresponds to the same ID of motion events EA, EB, and EC. Suchrelation data RD2 is transmitted to the image sensor device 1700A and1700B so that each of the three image sensor devices 1700A, 1700B, and1700C stores the relation data RD2 corresponding to the same ID. Itshould be noted that the relation data RD2 will replace the relationdata RD1 for the image sensor devices 1700A and 1700B since the data RD1and RD2 are associated with the same ID and the version of data RD2 isnew.

Later, when any image sensor device is enabled and detects a motionevent of a specific or any motion object, such image sensor device cangenerate a trigger signal to other adjacent image sensor device(s)indicated by the stored relation data. For example, as shown in FIG. 21, the image sensor device 1700A (but not limited) can send a triggersignal to the image sensor devices 1700B and 1700C based on theabove-mentioned relation data RD2 via wired/wireless communications.Once receiving the trigger signal, the image sensor devices 1700B and1700C can respectively exit a power saving mode and enters a monitoringmode so that the image sensor devices 1700B and 1700C can be ready todetect and monitor the motion/movement of the specific or any motionobject so as to pre-record one or more monitoring images.

Further, in another embodiment, the image sensor devices 1700B and 1700Cmay sequentially enter the monitoring mode. For example, the relationdata RD2 may also record the information of timestamps tA, tB, and tC,and based on such relation data RD2 the image sensor device 1700A canidentify which image sensor device is a next one to be ready to detectthe movement of the specific or any motion object and then may send atrigger signal to only the image sensor device 1700B. Once receiving thetrigger signal, the image sensor device 1700B enters the monitoring modewhile the image sensor device 1700C is kept in the power saving modesince the trigger is not yet transmitted to the image sensor device1700C. Then, when the image sensor device 1700B also detects themovement of the specific or any motion object, it sends a trigger signalto the image sensor device 1700C based on the relation data RD2 whichindicates that the timestamp tC is later than the timestamp tB. Oncereceiving the trigger signal, the image sensor device 1700C enters themonitoring mode. That is, adjacent image sensor devices can be arrangedto simultaneously enter the monitoring mode or can sequentially enterthe monitoring mode one by one based on the relation data. This can beconfigured or adjusted by the user's preferred setting.

Further, in other embodiments, the operation of sending the triggersignal to other adjacent image sensor device(s) can be also controlledand executed by the backend system 1701. That is, the relation data suchas RD2 can be stored by the backend system 1701. When the image sensordevice 1700A detects a motion object, the backend system 1701 can sendthe trigger signal to the image sensor device 1700B and/or the imagesensor device 1700C based on the relation data RD2.

Further, in one embodiment, the backend system 1701 can be arranged forautomatically generating and outputting a ranking list of the adjacentimage sensor devices 1700A, 1700B, 1700C for the user according to therelation data RD2. Such ranking list does not comprise one or more imagesensor devices which are not adjacent to any one of the group of imagesensor devices 1700A, 1700B, 1700C. The backend system 1701 can generatedifferent ranking lists of different groups of image sensor devices forthe user according to multiple different sets of relation data, and thedifferent ranking lists of different groups of image sensor devices canbe combined with the raking lists of the ROIs of each image sensordevice. Thus, for example, when the user presses/clicks/touches a likeicon for a notification/alarm video of a specific image sensor (or aspecific ROI of the specific image sensor device), one or more imagesensor devices, which are adjacent to the specific image sensor device,can be ranked at the top of a ranking list, and one or more ROIs, whichare associated with the same/similar features of the specific ROI, canbe ranked at the front of ROI(s), that are not associated with thesame/similar features, in the ranking list. All the operations mentionedabove can be controlled by the backend system 1701 or each image sensordevice and are not detailed again for brevity.

Additionally, in one embodiment, the location of a camera devicecomprising an image sensor device may be away from those of otherdevices. FIG. 22 and FIG. 23 are diagrams respectively showing differentexamples of the image sensor devices according to different embodimentsof the invention. As shown in FIG. 22 , the image sensor device 1700Cmay be away from other image sensor devices 1700A, 1700B, and theprocessing circuit 1710C determines that the device 1700 does not have arelation with the devices 1700A, 1700B if the image sensor device 1700Cdoes not detect one or more motion event having the features which areidentical or similar to that of the motion event detected by the otherimage sensor devices 1700A, 1700B. In this situation, neither theprocessing circuit 1710A nor processing circuit 1710B sends the triggersignal to the image sensor device 1700C. Instead, as shown in theexample of FIG. 23 , the image sensor device 1700C is away from otherimage sensor devices 1700A, 1700B, and the processing circuit 1710Cdetermines that the device 1700 exactly has a relation with the devices1700A, 1700B since the image sensor device 1700C detects one or moremotion events having the features which are identical or similar to thatof the motion event detected by the other image sensor devices 1700A,1700B. For example, the image sensor device 1700C also detects themotion events of the same human-shape motion object at a non-adjacenttimestamp. In this situation, the processing circuit 1710A or processingcircuit 1710B is arranged to send the trigger signal to the image sensordevice 1700C.

Further, it should be noted that the above-mentioned operations can beapplied into detecting and monitoring one or more vehicles. The featureof a vehicle device may further comprise at least one of the vehicle'slicense plate, color, size, shape, height, etc.

To make readers more clearly understand the operation of merging theimage streams of different image sensor devices and the operation ofcontrolling an image sensor device pre-recording the image streams, FIG.24 is provided. FIG. 24 is a flowchart diagram of the method of mergingimage streams of different image sensor devices and pre-recoding imagestreams according to an embodiment of the invention. The description ofsteps is described in the following:

-   -   Step S2400: start;    -   Step S2405: a first image sensor device captures image streams,        detects a first motion event associated with a first motion        object, and generates feature information of the first motion        event;    -   Step S2410: the first image sensor device determines whether the        feature information of the first motion event is similar or        identical to that of a second motion event generated by a second        image sensor device; if the feature information is        similar/identical, then the flow proceeds to Step S2415,        otherwise, the flow proceeds to Step S2420;    -   Step S2415: the first image sensor device uses the        identification information of the second motion event as the        identification information of the first motion event;    -   Step S2420: the first image sensor device uses different        identification information as the identification information of        the first motion event;    -   Step S2425: merge the image streams of the first and second        motion event if the identification information is identical or        similar;    -   Step S2430: generate and store the relation data of the first        and second image sensor device based on the same identification        data;    -   Step S2435: send the trigger signal to one of the first and        second image sensor devices to make one image sensor device        enter a monitoring mode to pre-record monitoring images when the        another image sensor device is enabled and detects a motion        object; and    -   Step S2440: End.

Those skilled in the art will readily observe that numerousmodifications and alterations of the device and method may be made whileretaining the teachings of the invention. Accordingly, the abovedisclosure should be construed as limited only by the metes and boundsof the appended claims.

What is claimed is:
 1. A motion detection method applied into an imagesensor device, comprising: capturing a plurality of monitoring imagesthrough the image sensor device; generating a plurality of regions ofinterest (ROIs) for each of the plurality of monitoring images;receiving a user's feedback in favor of at least one region of interest(ROI); selecting at least one ROI corresponding to a highest priority inpriority levels of the plurality of ROIs to be displayed to the user;transmitting a first notification to the user to notify the user of afirst motion event occurring within a first ROI according to a firstnotification mode; and transmitting a second notification to the user tonotify the user of a second motion event occurring within a second ROIaccording to a second notification mode; wherein the first notificationmode is more urgent than the second notification mode when a prioritylevel of the first ROI is higher than a priority level of the secondROI.
 2. The motion detection method of claim 1, further comprising: foreach ROI: detecting whether at least one motion event occurs within theeach ROI; and determining a priority level of the each ROI according toat least one feature information of the at least one motion event. 3.The motion detection method of claim 2, further comprising: detectingwhether the at least one motion event occurs within the each ROI bydetecting whether one or more motion objects occur within the each ROI;and comparing one or more feature information of the one or more motionobjects with candidate feature information to determine the at least onefeature information of the at least one motion event.
 4. The motiondetection method of claim 3, further comprising: tagging at least oneunique identification information for the at least one motion event. 5.The motion detection method of claim 1, further comprising: assigningdifferent identification information for a plurality of motion eventshaving at least one identical feature information; classifying theplurality of motion events having the at least one identical featureinformation into a same event group; and in response to the user'sfeedback for a particular motion event in the plurality of motionevents, determining one or more ROIs in which the plurality of motionevents occur according to the different identification information, andthen adjusting one or more priority levels of the one or more ROIsaccording to an identical adjustment of the user's feedback.
 6. Themotion detection method of claim 1, further comprising: When detectingthe first motion event within the first ROI on a first monitoring imagegenerated from the image sensor device, generating a first featureinformation of the first motion event and a first timestamp; searching asystem storage, electrically coupled to another different image sensordevice, according to the first feature information and the firsttimestamp, to obtain the second motion event within the second ROI on asecond monitoring image generated from the another different imagesensor device; and using an identification information of the secondmotion event as an identification information of the first motion eventto combine the second motion event with the first motion event.
 7. Themotion detection method of claim 6, further comprising: in response to auser request corresponding to the second motion event, generating andoutputting at least one image of the first motion event and at least oneimage of the second motion event for the user according to theidentification information of the first motion event which is identicalto the identification information of the second motion event.
 8. Themotion detection method of claim 6, further comprising: storing arelation between image sensor device and the another different imagesensor device when the identification information of the second motionevent is equal to the identification information of the first motionevent; receiving a trigger signal from the another different imagesensor device, the trigger signal being generated when the anotherdifferent image sensor device detects the second motion event; andpowering on the image sensor device to sense one or more monitoringimages according to the trigger signal and the relation, to pre-recordthe one or more monitoring images.
 9. The motion detection method ofclaim 8, further comprising: automatically generating and outputting aranking list of a plurality of image sensor devices for the useraccording to one or more relations between the plurality of image sensordevices.
 10. An image sensor device, comprising: a sensing circuit, forcapturing a plurality of monitoring images and generating a plurality ofregions of interest (ROIs) for each of the plurality of monitoringimages; and a processing circuit, coupled to the sensing circuit,configured for receiving a user's feedback in favor of at least oneregion of interest (ROI) and selecting at least one ROI corresponding toa highest priority in priority levels of the plurality of ROIs to bedisplayed to the user; wherein the processing circuit is furtherarranged for: transmitting a first notification to the user to notifythe user of a first motion occurring within a first ROI according to afirst notification mode; and transmitting a second notification to theuser to notify the user of a second motion occurring within a second ROIaccording to a second notification mode; the first notification mode ismore urgent than the second notification mode when a priority level ofthe first ROI is higher than a priority level of the second ROI.
 11. Theimage sensor device of claim 10, wherein the processing circuit isarranged for detecting whether at least one motion event occurs withineach ROI and determining a priority level of the each ROI according toat least one feature information of the at least one motion event. 12.The image sensor device of claim 11, wherein the processing circuit isarranged for: detecting whether the at least one motion event occurswithin the each ROI by detecting whether one or more motion objectsoccur within the each ROI; and comparing one or more feature informationof the one or more motion objects with candidate feature information todetermine the at least one feature information of the at least onemotion event.
 13. The image sensor device of claim 12, wherein theprocessing circuit is further arranged for: tagging at least one uniqueidentification information for the at least one motion event.
 14. Theimage sensor device of claim 10, wherein the processing circuit isfurther arranged for: When detecting the first motion event within thefirst ROI on a first monitoring image generated from the image sensordevice, generating a first feature information of the first motion eventand a first timestamp; searching a system storage, electrically coupledto another different image sensor device, according to the first featureinformation and the first timestamp, to obtain the second motion eventwithin the second ROI on a second monitoring image generated from theanother different image sensor device; and using an identificationinformation of the second motion event as an identification informationof the first motion event to combine the second motion event with thefirst motion event.
 15. The image sensor device of claim 14, wherein theprocessing circuit is further arranged for: in response to a userrequest corresponding to the second motion event, generating andoutputting at least one image of the first motion event and at least oneimage of the second motion event for the user according to theidentification information of the first motion event which is identicalto the identification information of the second motion event.
 16. Theimage sensor device of claim 14, wherein the processing circuit isfurther arranged for: storing a relation between image sensor device andthe another different image sensor device when the identificationinformation of the second motion event is equal to the identificationinformation of the first motion event; receiving a trigger signal fromthe another different image sensor device, the trigger signal beinggenerated when the another different image sensor device detects thesecond motion event; and powering on the image sensor device to senseone or more monitoring images according to the trigger signal and therelation, to pre-record the one or more monitoring images.
 17. The imagesensor device of claim 16, wherein the processing circuit is furtherarranged for: automatically generating and outputting a ranking list ofa plurality of image sensor devices for the user according to one ormore relations between the plurality of image sensor devices.
 18. Animage sensor device, comprising: a sensing circuit, for capturing aplurality of monitoring images and generating a plurality of regions ofinterest (ROIs) for each of the plurality of monitoring images; and aprocessing circuit, coupled to the sensing circuit, configured forreceiving a user's feedback in favor of at least one region of interest(ROI) and selecting at least one ROI in a highest priority to bedisplayed to the user; wherein the processing circuit is furtherarranged for: assigning different identification information for aplurality of motion events having at least one identical featureinformation; classifying the plurality of motion events having the atleast one identical feature information into a same event group; and inresponse to the user's feedback for a particular motion event in theplurality of motion events, determining one or more ROIs in which theplurality of motion events occur according to the differentidentification information, and then adjusting one or more prioritylevels of the one or more ROIs according to an identical adjustment ofthe user's feedback.